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Updated: Nov 22, 2025
Simulator Training for Endovascular Neurosurgery
Published on: May 6, 2020
Transesophageal Echocardiography Simulator Training: A Systematic Review and Meta-analysis of Randomized Controlled
Satoshi Jujo1, Atsushi Nakahira, Yuki Kataoka
1From the SimTiki Simulation Center (S.J., A.N., B.W.B.), John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI; Department of Anesthesiology (S.J., H.M.), Kameda General Hospital, Chiba; Department of Critical Care Medicine (A.N.), Nara Prefecture General Medical Center, Nara; Department of Respiratory Medicine (Y.K.) and Hospital Care Research Unit (Y.K., H.T.), Hyogo Prefectural Amagasaki General Medical Center, Hyogo; Department of Psychiatry (M.B.), Seichiryo Hospital; Department of Psychiatry (M.B.), Nagoya University Graduate School of Medicine, Aichi; Department of Nephrology and Dialysis (Y.T.), Kyoritsu Hospital, Hyogo; and Department of Healthcare Epidemiology (Y.T.), School of Public Health in the Graduate School of Medicine, and Medical Education Center (S.O.), Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Summary Statement:
We aimed to assess the learning effects of novice transesophageal echocardiography (TEE) simulator training and to identify gaps in existing studies. We performed a systematic review and meta-analysis of randomized controlled trials (RCTs) comparing the learning effects of novice TEE training with versus without simulators, searching published articles and proceedings in 6 major databases in June 2019. We included 9 RCTs (268 participants). Compared with nonsimulator training, TEE simulator training resulted in higher skill and knowledge posttraining test scores with large effect sizes (standardized mean difference = 0.81 for skill, 1.61 for knowledge; low-certainty evidence) and higher training satisfaction with a small effect size (standardized mean difference = 0.36; very low-certainty evidence). No RCTs reported training budget or patient outcomes. Additional well-designed studies with low risk of bias and large sample sizes are needed to provide reliable and robust findings and develop more effective TEE simulation-based training curricula.
